Satellite anti-collision method and device and computer readable storage medium

Abstract

The invention discloses a satellite anti-collision method and device and a computer readable storage medium. Relates to the technical field of satellites. The method comprises the following steps: acquiring obstacle information of obstacles in a movable range of a target satellite; according to the obstacle information and the target satellite information of the target satellite, the probability that the target satellite does not collide with the obstacle is calculated; calculating an energy value consumed by the target satellite according to the height of the target satellite adjusted for avoiding collision; constructing a consumption calculation model according to the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite; and solving the consumption calculation model through a genetic algorithm by taking the minimum consumption as a target, and determining the adjustment height of the target satellite. Therefore, the technical problem that fuel consumption is too high when the satellite avoids the obstacle is solved.

Description

Technical Field

[0001] The present application relates to the field of satellite technology, and in particular to a satellite collision avoidance method, device and computer-readable storage medium. Background Art

[0002] At present, the number of low-orbit satellites is increasing, and orbital resources are becoming increasingly scarce. At the same time, there is some space debris in space. For their own safety, low-orbit satellites should have the ability to deal with collision risks.

[0003] Each satellite has its own orbit, and the satellites are running at a fast speed, but it is very likely that some satellites will deviate from their normal orbits. At this time, satellites that are operating normally in their own orbits will obtain the trajectories of nearby satellites or obstacles such as space debris in real time through multi-source data fusion such as space-based radars and optical sensors, and avoid them in time. However, satellites will increase propellant consumption when dodging, and frequent maneuvers will cause the fuel to run out of time. Satellites with insufficient fuel will face the risk of uncontrolled orbital decay, shutdown of functional modules, and even becoming new collision sources.

[0004] The publication number is CN119519812A, and the name is "Method, device and storage medium for adjusting the operation trajectory", which relates to the field of communication satellite technology. It can adjust the operation trajectory of the communication satellite according to the content of the first signal, so as to avoid the flying objects on the original operation orbit. The operation of manual intervention is omitted, and the communication satellite can autonomously avoid the flying objects. In the face of emergency situations, it can effectively avoid them in the first time. The method includes: receiving a first signal, the first signal includes a detection signal emitted by the communication satellite, a signal reflected back by the flying object and / or a detection signal of other communication satellites; wherein the flying object and the communication satellite are on the same operation trajectory; according to the first signal, adjusting the operation trajectory of the communication satellite.

[0005] The publication number is CN111861859A, and the name is a space debris collision warning method, which is applied to a space debris positioning system and a warning system; wherein the warning system: uses the space debris observation information detected by the microwave radar on the spacecraft, uses the spacecraft orbit information, calculates the relative motion trajectory of the space debris in the spacecraft orbit coordinate system, and calculates the minimum distance of the space debris relative to the spacecraft within the future time T. Through multiple judgments on the minimum distance, a warning message is given, and an orbit avoidance program for avoiding collision is initiated.

[0006] With respect to the technical problem of excessive fuel consumption when a satellite avoids obstacles in the above-mentioned prior art, no effective solution has been proposed yet. Summary of the invention

[0007] The embodiments of the present application provide a satellite collision avoidance method, device, and computer-readable storage medium to at least solve the technical problem in the prior art of excessive fuel consumption when a satellite avoids obstacles.

[0008] According to one aspect of an embodiment of the present application, a satellite collision avoidance method is provided, comprising: obtaining obstacle information of obstacles within a movable range of a target satellite, wherein the obstacle information includes position information, speed information and volume information of the obstacle; calculating the probability that the target satellite does not collide with the obstacle based on the obstacle information and target satellite information of the target satellite, wherein the target satellite information includes position information, speed information and volume information of the target satellite; calculating the energy value consumed by the target satellite based on the height adjusted by the target satellite to avoid collision; constructing a consumption calculation model based on the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite; and solving the consumption calculation model through a genetic algorithm with the minimum consumption as the goal to determine the adjusted height of the target satellite.

[0009] According to another aspect of an embodiment of the present application, a satellite collision avoidance device is also provided, including: an information acquisition module, used to acquire obstacle information of obstacles within the movable range of the target satellite, wherein the obstacle information includes the position information, speed information and volume information of the obstacle; a probability calculation module, used to calculate the probability that the target satellite does not collide with the obstacle based on the obstacle information and the target satellite information of the target satellite, wherein the target satellite information includes the position information, speed information and volume information of the target satellite; an energy value calculation module, used to calculate the energy value consumed by the target satellite based on the height adjusted by the target satellite to avoid collision; a model construction module, used to construct a consumption calculation model based on the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite; and an altitude determination module, used to solve the consumption calculation model through a genetic algorithm with the minimum consumption as the goal, and determine the adjusted altitude of the target satellite.

[0010] According to another aspect of an embodiment of the present application, a satellite collision avoidance device is also provided, including: a processor; and a memory connected to the processor, for providing the processor with instructions for processing the following processing steps: obtaining obstacle information of obstacles within the movable range of the target satellite, wherein the obstacle information includes the position information, speed information and volume information of the obstacle; calculating the probability that the target satellite does not collide with the obstacle based on the obstacle information and the target satellite information of the target satellite, wherein the target satellite information includes the position information, speed information and volume information of the target satellite; calculating the energy value consumed by the target satellite based on the height adjusted by the target satellite to avoid collision; constructing a consumption calculation model based on the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite; and solving the consumption calculation model through a genetic algorithm with the minimum consumption as the goal to determine the adjusted height of the target satellite.

[0011] According to another aspect of an embodiment of the present application, there is also provided an integrated electronic system, including a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above method.

[0012] In the embodiment of the present application, the obstacle information (including position, speed and volume) within the movable range of the target satellite is used to determine the collision probability between the target satellite and the obstacle and the energy value consumed to avoid the collision, and a consumption calculation model is constructed based on this, so that according to the consumption calculation model, the moving distance of the target satellite is determined with the goal of minimizing energy consumption and maximizing the probability of no collision. Therefore, the target satellite can avoid obstacles according to the moving distance, achieving both avoiding collisions and reducing energy consumption, thereby extending the service life of the satellite and avoiding various risks caused by premature exhaustion of fuel. This solves the technical problem of excessive fuel consumption when satellites avoid obstacles in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings: Figure 1 is a hardware structure block diagram for implementing the satellite according to Embodiment 1 of the present application; Figure 2 is a schematic diagram of a satellite constellation according to Embodiment 1 of the present application; Figure 3 is a schematic flow chart of a satellite collision avoidance method according to the first aspect of Embodiment 1 of the present application; Figure 4 is a schematic diagram of the satellite collision avoidance device according to Embodiment 2 of the present application; and Figure 5 This is a schematic diagram of the satellite anti-collision device according to Example 3 of the present application. DETAILED DESCRIPTION

[0014] In order to enable those skilled in the art to better understand the technical solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only embodiments of a part of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work should fall within the scope of protection of the present application.

[0015] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0016] Example 1 According to this embodiment, a method embodiment of a satellite collision avoidance method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0017] Figure 1 A schematic diagram showing the hardware architecture of the satellite. Figure 1 As shown, the satellite includes a satellite computer, which includes: a processor, a memory, a bus management module and a communication interface. The memory is connected to the processor, so that the processor can access the memory, read the program instructions stored in the memory, read data from the memory or write data to the memory. The bus management module is connected to the processor and is also connected to a bus such as a CAN bus. Therefore, the processor can communicate with the satellite-borne peripherals connected to the bus through the bus managed by the bus management module. In addition, the processor is also connected to communication devices such as cameras, star sensors, measurement and control transponders, and data transmission equipment via the communication interface. It can be understood by those skilled in the art that Figure 1The structure shown is for illustration only and does not limit the structure of the above electronic device. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0018] It should be noted that Figure 1 The one or more processors and / or other data processing circuits shown in the figure may generally be referred to as "data processing circuits" herein. The data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuit may be a single independent processing module, or may be incorporated in whole or in part into any of the other components in the computing device. As involved in the embodiments of the present application, the data processing circuit acts as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0019] Figure 1 The memory shown in the figure can be used to store software programs and modules of application software, such as the program instruction / data storage device corresponding to the satellite collision avoidance method in the embodiment of the present application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, the satellite collision avoidance method of the above application is realized. The memory may include a high-speed random access memory and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory.

[0020] It should be noted that, in some optional embodiments, the above Figure 1 The devices shown may include hardware elements (including circuits), software elements (including computer code stored on a computer-readable medium), or a combination of both hardware and software elements. Figure 1 This is merely one example of a particular embodiment and is intended to illustrate the types of components that may be present in the above described apparatus.

[0021] Figure 2 is a schematic diagram of a satellite constellation according to this embodiment. Figure 2 As shown, there are multiple obstacles such as multiple satellites or space debris flying in each satellite orbit. S 1~ S m , when the target satellite S 0 When flying in its own orbit, it may encounter abandoned satellites or space debris and collide with them, so the target satellite S 0 will periodically monitor whether there are obstacles within the movable range, and if there are obstacles, avoid them with minimal consumption. S 0 can be SARSatellite (radar satellite).

[0022] Under the above operating environment, according to the first aspect of this embodiment, a satellite collision avoidance method is provided. The method comprises: Figure 1 The star service computer implementation shown in . Figure 3 A schematic diagram showing the process of the method is shown in FIG. Figure 3 As shown, the method includes: S 302: Obtain obstacle information of obstacles within the movable range of the target satellite, wherein the obstacle information includes position information, speed information, and volume information of the obstacles; S 304: Calculate the probability that the target satellite does not collide with the obstacle according to the obstacle information and the target satellite information of the target satellite, wherein the target satellite information includes the position information, speed information and volume information of the target satellite; S 306: Calculate the energy value consumed by the target satellite according to the altitude adjusted by the target satellite to avoid collision; S 308: constructing a consumption calculation model according to the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite; and S 310: With the minimum consumption as the goal, the consumption calculation model is solved by genetic algorithm to determine the adjustment height of the target satellite.

[0023] Specifically, the target satellite S 0 can be U ~ L Move within the range of U Indicates the maximum distance that the target satellite can escape from its current orbit and move upward; L Indicates the maximum distance that the target satellite can escape from the current orbit and move downward. S 0, there may be other satellites or space debris as obstacles that hinder the target satellite S 0 moves.

[0024] Thus, the target satellite S 0's satellite computer obtains the information about the target satellite from the orbit parameter file and other data that records the information about the satellite or space debris. S Obstacles within the movable range of 0 S 1~ S m Obstacle information, such as the location information, speed information and volume information of the obstacle. S 1~ S mIt could be a satellite or space junk.

[0025] Furthermore, the satellite computer determines the target satellite S 0 target satellite information, including the target satellite's position information, speed information and volume information. Then the satellite computer S 0 target satellite information and obstacle information, calculate the target satellite S 0 and various obstacles S 1~ S m The probability of no collision.

[0026] Furthermore, when the target satellite S 0 If there is an obstacle ahead during flight, the flight altitude needs to be adjusted. S 0 is the height (i.e., distance) adjusted to avoid obstacles, and the energy value consumed by the target satellite (e.g., fuel mass) is calculated. S 0 The energy consumed for moving upward and moving downward is different, and can be set through experience. For example, the energy consumed for moving upward is 0.5 kg / 100 km , the energy consumed by moving downward is 0.3 kg / 100 km .

[0027] Furthermore, the satellite computer constructs a consumption calculation model according to the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite, wherein the consumption calculation model is used to indicate the ratio between the probability that the target satellite does not collide with the obstacle and the energy value consumed when the altitude is adjusted, wherein the satellite computer constructs the consumption calculation model according to the following formula : , in represents the altitude (i.e., distance) that the target satellite adjusts to avoid collision, Ps ( ) represents the probability that the target satellite will not collide after adjusting its altitude. E ( ) represents the energy consumed by the target satellite to adjust its altitude. K Indicates the error value.

[0028] Therefore, the star service computer uses the consumption calculation model to maximize the probability of no collision and minimize the energy consumption (i.e., maximum), determines the altitude (i.e., distance) to which the target satellite should be adjusted.

[0029] Furthermore, the star service computer uses genetic algorithms to solve the consumption calculation model with the goal of minimum consumption, so that Maximum, thereby determining the adjusted height (i.e., distance) of the target satellite. The genetic algorithm is as follows: First, the star service computer initializes the initial population of the genetic algorithm, where the initial population includes the initial individuals , ,..., The initial individual is used to indicate the adjustment height (i.e., distance) of the target satellite. The constraint condition for adjusting the height is greater than or equal to the maximum distance of upward movement. U , and is less than or equal to the maximum distance to move downward L .

[0030] After that, the star service computer will consume the calculation model As the initial individual , ,..., The fitness model of the initial individual , ,..., Substitute into the consumption calculation model respectively , k =1~ y .

[0031] The consumption calculation model is thus: .

[0032] Then the star service computer determines the fitness , the selection probability of each initial individual is calculated according to the fitness, and then the first number of initial individuals with higher selection probability are selected as the first individual, thereby generating the first population. Individuals with higher fitness are more likely to be selected. The method for calculating the selection probability can be, for example, the roulette wheel selection method.

[0033] The star service computer then determines a second number of individuals from the first population according to a preset crossover rate, performs a crossover operation on the individuals, generates new individuals (ie, second individuals), and thus the second individuals form a second population.

[0034] Afterwards, the star service computer determines a third number of individuals from the second population according to a preset mutation rate, performs mutation operations on the individuals, generates new individuals (ie, the third individuals), and thus the third individuals form a third population.

[0035] At this point, the first round of iteration of the genetic algorithm is completed.

[0036] For the second round of iteration, the star service computer inputs the third individual in the third population into the consumption calculation model to determine the fitness of each third individual. Then, the star service computer performs selection, crossover and mutation operations on the third individual in accordance with the steps in the first round of iteration to generate a new population. The second round of iteration of the genetic algorithm is now completed.

[0037] The star service computer then performs multiple rounds of iterative calculations according to the above steps until a preset number of iterations is reached.

[0038] For example, the number of iterations is preset to three, so the star service computer uses the individual with the highest fitness determined in the third round of iteration as the adjustment height.

[0039] As described in the background technology, at present, the number of low-orbit satellites is increasing, and orbital resources are becoming increasingly scarce. At the same time, there is some space junk in space. For their own safety, low-orbit satellites should have the ability to cope with collision risks. Each satellite has its own orbit, and the satellite runs at a fast speed, but it is very likely that some satellites have deviated from their normal orbits. At this time, satellites that are operating normally in their own orbits will obtain the trajectories of nearby satellites or obstacles such as space junk in real time through multi-source data fusion such as space-based radars and optical sensors, and avoid them in time. However, satellites will increase propellant consumption when dodging, and frequent maneuvers will cause fuel to run out of control in advance. Satellites with insufficient fuel will face the risk of uncontrolled orbital decay, shutdown of functional modules, and even becoming new collision sources.

[0040] In view of the technical problems described above, through the technical solution of the embodiment of the present application, the obstacle information (including position, speed and volume) within the movable range of the target satellite is used to determine the collision probability between the target satellite and the obstacle and the energy value consumed to avoid the collision, and a consumption calculation model is constructed based on this, so that according to the consumption calculation model, the moving distance of the target satellite is determined with the goal of minimizing energy consumption and maximizing the probability of no collision. Therefore, the target satellite can avoid obstacles according to the moving distance, achieving both avoiding collisions and reducing energy consumption, thereby extending the service life of the satellite and avoiding various risks caused by premature exhaustion of fuel. This solves the technical problem of excessive fuel consumption when satellites avoid obstacles in the prior art.

[0041] Optionally, the operation of calculating the probability that the target satellite does not collide with the obstacle based on the obstacle information and the target satellite information of the target satellite includes: calculating the minimum approach distance between the target satellite and the obstacle based on the position information of the target satellite and the position information of the obstacle; and calculating the probability that the target satellite does not collide with the obstacle based on the minimum approach distance and the speed information and volume information of the target satellite and the obstacle.

[0042] Specifically, the satellite computer determines that at the next moment, the target satellite S 0 location information ( x 0, y 0, z 0), and all obstacles S j Location information ( x j , y j , z j ). In the next moment, the target satellite S 0 location information ( x 0, y 0, z 0) can be the target satellite S 0 after adjusting the flight altitude. Then the satellite computer calculates the position information based on the position information ( x 0, y 0, z 0) and obstacles S j Location information ( x j , y j , z j ), calculate the target satellite S 0 On the flight trajectory after adjusting the flight altitude, S j Minimum approach distance d j : .

[0043] Thus, according to the above formula, the satellite computer traverses the target satellite S 0 All time points of flying on the flight track after adjusting the flight altitude t , respectively find the obstacles S j The corresponding minimum distance is used as the target satellite S 0 and obstacles S j Minimum approach distance d j .

[0044] Furthermore, the satellite computer uses the minimum approach distance d j As well as the speed information and volume information of the target satellite and the obstacle, the probability of no collision between the target satellite and the obstacle is calculated.

[0045] Therefore, this technical solution can accurately assess the probability of no collision by calculating the minimum approach distance between the target satellite and the obstacle and combining the speed information and volume information of both parties, making the calculation of the collision probability more comprehensive and accurate.

[0046] Optionally, the operation of calculating the probability that the target satellite and the obstacle do not collide based on the minimum approach distance and the speed information and volume information of the target satellite and the obstacle includes: calculating the probability that the target satellite and the obstacle do not collide based on the following formula: Ps : (1) (2) (3) (4) (5) in P j Indicates the target satellite and j The probability of a collision with an obstacle is m represents the number of obstacles, j =1~ m , T 0 indicates the volume information of the target satellite. T j Indicates j The volume information of obstacles, r 0 represents the equivalent radius of the target satellite, r j Indicates j The equivalent radius of an obstacle, V j Indicates the target satellite and j The relative speed of the obstacle, R j Indicates the target satellite and j The equivalent collision radius of obstacles, Indicates the target satellite and j The effective time window for the relative interaction of obstacles, d j Indicates the minimum approach distance, represents the speed error, Indicates position error.

[0047] Specifically, the satellite computer acquires the target satellite S 0 volume T 0 and various obstacles S j Volume Tj , and then use formula (5) according to the target satellite S 0 volume T 0 and various obstacles S j Volume T j , calculate the target satellites respectively S 0 equivalent radius r 0 and obstacles S j The equivalent radius r j , then calculate the target satellite S 0 equivalent radius r 0 and obstacles S j The equivalent radius r j The target satellite S 0 and obstacles S j The equivalent collision radius R j .

[0048] Furthermore, the satellite computer obtains the speed of the target satellite and each obstacle, and then calculates the target satellite according to the speed of the target satellite and each obstacle. S 0 respectively with each obstacle S j Relative speed V j Then the star service computer uses formula (4) according to the equivalent collision radius R j and relative speed V j , calculate the effective time window The effective time window Used to indicate the higher the relative speed, the target satellite S 0 and obstacles S j The shorter the encounter time, the smaller the chance of collision.

[0049] Furthermore, the satellite computer obtains the speed error determined according to the empirical value , using formula (3) according to the speed error And the effective time window Determining position error .

[0050] Furthermore, the satellite service computer uses formula (2) according to the effective time window , Position error , equivalent collision radiusR j , relative speed V j and minimum approach distance d j , calculate the target satellite S 0 and obstacles S j Probability of collision P j .in It represents the product of relative velocity and equivalent collision radius, reflecting the volume of collision area swept per unit time. Medium, minimum approach distance d j The smaller it is, the weaker the exponential decay is and the higher the collision probability is; It indicates the cumulative effect of speed error within the time window. The higher the speed or the longer the time window, the more obvious the error accumulation.

[0051] Furthermore, the satellite computer uses formula (1) according to the target satellite S 0 and obstacles S j Probability of collision P j , calculate the target satellite S 0 and obstacles S j The probability of no collision Ps .

[0052] Therefore, this technical solution makes the assessment of collision probability more comprehensive and accurate through the minimum approach distance, dynamic parameters such as the speed and volume of the target satellite and the obstacle, as well as the influence of speed error and position error.

[0053] Optionally, the operation of constructing a consumption calculation model according to the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite includes: The consumption calculation model is constructed according to the following formula : , in Indicates the altitude that the target satellite adjusts to avoid collision. Ps ( ) represents the probability that the target satellite will not collide after adjusting its altitude. E ( ) represents the energy consumed by the target satellite to adjust its altitude. K represents the error value. Therefore, the star service computer can use the consumption calculation model to maximize the probability of no collision and minimize the energy consumption (i.e., The maximum height of the target satellite is determined by calculating the energy consumption of the target satellite. Therefore, the technical solution uses the consumption calculation model constructed according to the probability of no collision and the energy consumption value to determine the moving distance of the target satellite, thereby ensuring the trade-off between safety and energy consumption at different adjustment heights, which not only ensures flight safety but also reduces unnecessary energy waste.

[0054] Optionally, with minimum consumption as the goal, a consumption calculation model is solved by a genetic algorithm to determine the operation of adjusting the height of the target satellite, including: determining the number of binary bits of an initial population composed of multiple chromosomes of the genetic algorithm according to the movable range and movement accuracy of the target satellite, wherein the movement accuracy is used to indicate the unit length of the target satellite's movement; generating a binary-based initial population according to the binary bit number, wherein the initial population is the initial adjustment height of the target satellite; and solving the consumption calculation model according to the initial population to determine the adjustment height of the target satellite.

[0055] Specifically, when the satellite service computer determines the adjustment altitude of the target satellite according to the genetic algorithm, it first generates an initial population, wherein each chromosome corresponding to the initial individual in the initial population is a binary string. Thus, the satellite service computer determines the number of binary bits of the chromosome binary string according to the movable range and movement accuracy of the target satellite. The movement accuracy is used to indicate the unit length of the target satellite movement, for example, 100km. Thus, the satellite service computer determines the number of binary bits of the initial population according to the following formula: n : , in U Indicates the maximum distance that the target satellite is adjusted upward. L represents the maximum distance that the target satellite is adjusted downward, where L is a negative number, SA Indicates the movement accuracy of the preset target satellite.

[0056] Furthermore, the star service computer will initialize the individual , ,..., (i.e., decimal numbers) are substituted into the consumption calculation model , k =1~ y .

[0057] The consumption calculation model is thus: .

[0058] Then the star service computer determines the fitness , the selection probability of each initial individual is calculated according to the fitness, and then the first number of initial individuals with higher selection probability are selected as the first individual, thereby generating the first population. Individuals with higher fitness are more likely to be selected. The method for calculating the selection probability can be, for example, the roulette wheel selection method.

[0059] Further, the satellite service computer generates the distance (decimal number) adjusted by the first individual in the first group, that is, the target satellite n Then, the star service computer determines a second number of individuals from the first population according to a preset crossover rate, performs a crossover operation on the chromosome binary strings corresponding to the multiple individuals, generates chromosome binary strings of new individuals (i.e., the second individuals), and thus the second individuals form the second population.

[0060] Then, the star service computer determines a third number of individuals from the second population according to a preset mutation rate, performs mutation operations on the chromosome binary strings corresponding to the multiple individuals, and generates chromosome binary strings of a new individual (i.e., the third individual). Then, the star service computer decodes each chromosome binary string using the following formula to determine the third individual (i.e., the adjustment height): , , in Indicates the precision parameter, which is a transitional value; Represents the chromosome binary string i Number of digits; n The number of bits representing the chromosome binary string.

[0061] Thus, the Star Service Computer organizes the third individual into a third group.

[0062] At this point, the first round of iteration of the genetic algorithm is completed.

[0063] For the second round of iteration, the star service computer inputs the third individual in the third population into the consumption calculation model to determine the fitness of each third individual. Then, according to the steps in the first round of iteration, the star service computer sequentially performs selection, crossover and mutation operations on the chromosome binary string of the third individual to generate a new population. At this point, the second round of iteration of the genetic algorithm is completed.

[0064] The star service computer then performs multiple rounds of iterative calculations according to the above steps until a preset number of iterations is reached.

[0065] For example, the number of iterations is preset to three, so the star service computer uses the individual with the highest fitness determined in the third round of iteration as the adjustment height.

[0066] Therefore, the technical solution avoids invalid solutions due to insufficient precision by ensuring that the step size of the height adjustment meets the preset accuracy requirements, and ensures the accuracy of the solution and avoids invalid iterations by converting the binary string into the actual adjustment height.

[0067] Optionally, the operation of determining the number of binary bits of an initial population composed of a plurality of chromosomes of a genetic algorithm according to the movable range and the moving accuracy of the target satellite includes: The number of binary digits of the initial population is determined according to the following formula n : , in U Indicates the maximum distance that the target satellite is adjusted upward. L Indicates the maximum distance to which the target satellite is adjusted downward. SA Indicates the moving accuracy of the target satellite.

[0068] Therefore, the technical solution can ensure that the adjustment height of each chromosome binary string has sufficient accuracy within the movable range of the target satellite through the calculated binary digits. This not only avoids the solution being too rough due to over-coarse coding, but also prevents the waste of computing resources caused by over-fine coding.

[0069] Optionally, the operation of determining the adjustment height of the target satellite includes: determining a chromosome binary string corresponding to the adjustment height according to the consumption calculation model; and decoding the chromosome binary string by the following formula to determine the adjustment height: , , in represents the precision parameter, Represents the chromosome binary string i Number of digits, n The number of bits representing the chromosome binary string.

[0070] Therefore, this technical solution is based on parameter restrictions such as the moving accuracy of the target satellite and the number of bits of the chromosome binary string, so that on the basis of satisfying these constraints, the decoding strategy can be flexibly adjusted so that the final adjusted height meets the actual needs.

[0071] In addition, according to a second aspect of this embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0072] Therefore, according to this embodiment, the obstacle information (including position, speed and volume) within the movable range of the target satellite is used to determine the collision probability between the target satellite and the obstacle and the energy value consumed to avoid the collision, and a consumption calculation model is constructed based on this, so that according to the consumption calculation model, the moving distance of the target satellite is determined with the goal of minimizing energy consumption and maximizing the probability of non-collision. Therefore, the target satellite can avoid obstacles according to the moving distance, achieving both avoiding collisions and reducing energy consumption, thereby extending the service life of the satellite and avoiding various risks caused by premature exhaustion of fuel. This solves the technical problem of excessive fuel consumption when satellites avoid obstacles in the prior art.

[0073] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0074] Through the above description of the implementation, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, or by hardware, but in many cases the former is a better implementation. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM , magnetic disk, optical disk), including several instructions for enabling a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in various embodiments of the present invention.

[0075] Example 2 Figure 4 The satellite collision avoidance device 400 according to this embodiment is shown, and the device 400 corresponds to the method according to the first aspect of embodiment 1. Figure 4As shown, the device 400 includes: an information acquisition module 410, which is used to acquire obstacle information of obstacles within the movable range of the target satellite, wherein the obstacle information includes the position information, speed information and volume information of the obstacle; a probability calculation module 420, which is used to calculate the probability that the target satellite does not collide with the obstacle according to the obstacle information and the target satellite information of the target satellite, wherein the target satellite information includes the position information, speed information and volume information of the target satellite; an energy value calculation module 430, which is used to calculate the energy value consumed by the target satellite according to the height adjusted by the target satellite to avoid collision; a model construction module 440, which is used to construct a consumption calculation model according to the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite; and an altitude determination module 450, which is used to solve the consumption calculation model by a genetic algorithm with the minimum consumption as the goal, and determine the adjusted altitude of the target satellite.

[0076] Optionally, the probability calculation module 420 includes: a first calculation submodule, used to calculate the minimum approach distance between the target satellite and the obstacle based on the position information of the target satellite and the position information of the obstacle; and a second calculation submodule, used to calculate the probability that the target satellite and the obstacle do not collide based on the minimum approach distance and the speed information and volume information of the target satellite and the obstacle.

[0077] Optionally, the energy value calculation module 430 includes a third calculation submodule, which is used to calculate the probability that the target satellite and the obstacle do not collide according to the following formula: Ps : (1) (2) (3) (4) (5) in P j Indicates the target satellite and j The probability of a collision with an obstacle is m represents the number of obstacles, j =1~ m , T 0 indicates the volume information of the target satellite. T j Indicates j The volume information of obstacles, r 0 represents the equivalent radius of the target satellite, r j Indicates j The equivalent radius of an obstacle, Vj Indicates the target satellite and j The relative speed of the obstacle, R j Indicates the target satellite and j The equivalent collision radius of obstacles, Indicates the target satellite and j The effective time window for the relative interaction of obstacles, d j Indicates the minimum approach distance, represents the speed error, Indicates position error.

[0078] Optionally, the model building module 440 includes: a fourth calculation submodule, which is used to build a consumption calculation model according to the following formula: : , in Indicates the altitude that the target satellite adjusts to avoid collision. Ps ( ) represents the probability that the target satellite will not collide after adjusting its altitude. E ( ) represents the energy consumed by the target satellite to adjust its altitude. K Indicates the error value.

[0079] Optionally, the altitude determination module 450 includes: a first determination submodule, used to determine the number of binary bits of an initial population composed of multiple chromosomes of the genetic algorithm according to the movable range and movement accuracy of the target satellite, wherein the movement accuracy is used to indicate the unit length of the movement of the target satellite; a second determination submodule, used to generate a binary-based initial population according to the number of binary bits, wherein the initial population is an initial adjustment altitude of the target satellite; and a third determination submodule, used to solve the consumption calculation model according to the initial population to determine the adjustment altitude of the target satellite.

[0080] Optionally, the first determination submodule includes: a first determination unit, configured to determine the number of binary digits of the initial population according to the following formula: n : , in U Indicates the maximum distance that the target satellite is adjusted upward. L Indicates the maximum distance to which the target satellite is adjusted downward. SA Indicates the moving accuracy of the target satellite.

[0081] Optionally, the third determination submodule includes: a second determination unit, used to determine the chromosome binary string corresponding to the adjustment height according to the consumption calculation model; and a third determination unit, used to decode the chromosome binary string through the following formula to determine the adjustment height: , , in represents the precision parameter, Represents the chromosome binary string i Number of digits, n The number of bits representing the chromosome binary string.

[0082] Therefore, according to this embodiment, the obstacle information (including position, speed and volume) within the movable range of the target satellite is used to determine the collision probability between the target satellite and the obstacle and the energy value consumed to avoid the collision, and a consumption calculation model is constructed based on this, so that according to the consumption calculation model, the moving distance of the target satellite is determined with the goal of minimizing energy consumption and maximizing the probability of non-collision. Therefore, the target satellite can avoid obstacles according to the moving distance, achieving both avoiding collisions and reducing energy consumption, thereby extending the service life of the satellite and avoiding various risks caused by premature exhaustion of fuel. This solves the technical problem of excessive fuel consumption when satellites avoid obstacles in the prior art.

[0083] Example 3 Figure 5 The satellite collision avoidance device 500 according to this embodiment is shown, and the device 500 corresponds to the method according to the first aspect of embodiment 1. Figure 5 As shown, the device 500 includes: a processor 510; and a memory 520, which is connected to the processor 510 and is used to provide the processor 510 with instructions for processing the following processing steps: obtaining obstacle information of obstacles within the movable range of the target satellite, wherein the obstacle information includes the position information, speed information and volume information of the obstacle; calculating the probability that the target satellite does not collide with the obstacle according to the obstacle information and the target satellite information of the target satellite, wherein the target satellite information includes the position information, speed information and volume information of the target satellite; calculating the energy value consumed by the target satellite according to the height adjusted by the target satellite to avoid collision; constructing a consumption calculation model according to the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite; and solving the consumption calculation model by a genetic algorithm with the minimum consumption as the goal to determine the adjusted height of the target satellite.

[0084] Optionally, the operation of calculating the probability that the target satellite does not collide with the obstacle based on the obstacle information and the target satellite information of the target satellite includes: calculating the minimum approach distance between the target satellite and the obstacle based on the position information of the target satellite and the position information of the obstacle; and calculating the probability that the target satellite does not collide with the obstacle based on the minimum approach distance and the speed information and volume information of the target satellite and the obstacle.

[0085] Optionally, the operation of calculating the probability that the target satellite and the obstacle do not collide based on the minimum approach distance and the speed information and volume information of the target satellite and the obstacle includes: calculating the probability that the target satellite and the obstacle do not collide based on the following formula: Ps : (1) (2) (3) (4) (5) in P j Indicates the target satellite and j The probability of a collision with an obstacle is m represents the number of obstacles, j =1~ m , T 0 indicates the volume information of the target satellite. T j Indicates j The volume information of obstacles, r 0 represents the equivalent radius of the target satellite, r j Indicates j The equivalent radius of an obstacle, V j Indicates the target satellite and j The relative speed of the obstacle, R j Indicates the target satellite and j The equivalent collision radius of obstacles, Indicates the target satellite and j The effective time window for the relative interaction of obstacles, d j Indicates the minimum approach distance, represents the speed error, Indicates position error.

[0086] Optionally, the operation of constructing a consumption calculation model according to the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite includes: constructing the consumption calculation model according to the following formula : , in Indicates the altitude that the target satellite adjusts to avoid collision. Ps ( ) represents the probability that the target satellite will not collide after adjusting its altitude. E ( ) represents the energy consumed by the target satellite to adjust its altitude. K Indicates the error value.

[0087] Optionally, with minimum consumption as the goal, a consumption calculation model is solved by a genetic algorithm to determine the operation of adjusting the height of the target satellite, including: determining the number of binary bits of an initial population composed of multiple chromosomes of the genetic algorithm according to the movable range and movement accuracy of the target satellite, wherein the movement accuracy is used to indicate the unit length of the target satellite's movement; generating a binary-based initial population according to the binary bit number, wherein the initial population is the initial adjustment height of the target satellite; and solving the consumption calculation model according to the initial population to determine the adjustment height of the target satellite.

[0088] Optionally, the operation of determining the number of binary digits of the initial population composed of a plurality of chromosomes of the genetic algorithm according to the movable range and the moving accuracy of the target satellite includes: determining the number of binary digits of the initial population according to the following formula: n : , in U Indicates the maximum distance that the target satellite is adjusted upward. L Indicates the maximum distance to which the target satellite is adjusted downward. SA Indicates the moving accuracy of the target satellite.

[0089] Optionally, the operation of determining the adjustment height of the target satellite includes: determining a chromosome binary string corresponding to the adjustment height according to the consumption calculation model; and decoding the chromosome binary string by the following formula to determine the adjustment height: , , in represents the precision parameter, Represents the chromosome binary string i Number of digits, n The number of bits representing the chromosome binary string.

[0090] Therefore, according to this embodiment, the obstacle information (including position, speed and volume) within the movable range of the target satellite is used to determine the collision probability between the target satellite and the obstacle and the energy value consumed to avoid the collision, and a consumption calculation model is constructed based on this, so that according to the consumption calculation model, the moving distance of the target satellite is determined with the goal of minimizing energy consumption and maximizing the probability of non-collision. Therefore, the target satellite can avoid obstacles according to the moving distance, achieving both avoiding collisions and reducing energy consumption, thereby extending the service life of the satellite and avoiding various risks caused by premature exhaustion of fuel. This solves the technical problem of excessive fuel consumption when satellites avoid obstacles in the prior art.

[0091] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0092] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0093] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0094] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0095] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0096] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk, etc. Various media that can store program codes.

[0097] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A satellite collision avoidance method, characterized in that: include: Obtaining obstacle information within the movable range of the target satellite, wherein the obstacle information includes position information, speed information, and volume information of the obstacle; Calculating the probability that the target satellite does not collide with the obstacle according to the obstacle information and the target satellite information, wherein the target satellite information includes the position information, speed information and volume information of the target satellite; Calculating the energy value consumed by the target satellite according to the altitude adjusted by the target satellite to avoid collision; constructing a consumption calculation model according to the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite; and Taking minimum consumption as the goal, the consumption calculation model is solved by a genetic algorithm to determine the adjustment height of the target satellite, wherein: The operation of calculating the probability that the target satellite does not collide with the obstacle based on the obstacle information and the target satellite information includes: calculating the minimum approach distance between the target satellite and the obstacle based on the position information of the target satellite and the position information of the obstacle; and calculating the probability that the target satellite does not collide with the obstacle based on the minimum approach distance and the speed information and volume information of the target satellite and the obstacle.

2. The method according to claim 1, characterized in that The operation of calculating the probability that the target satellite and the obstacle do not collide according to the minimum approach distance and the speed information and volume information of the target satellite and the obstacle includes: The probability that the target satellite and the obstacle do not collide is calculated according to the following formula: Ps : （1） （2） （3） （4） （5） in P j Indicates that the target satellite is j The probability of collision with obstacles is m represents the number of obstacles, j =1~ m , T 0 represents the volume information of the target satellite, T j Indicates the j The volume information of obstacles, r 0 represents the equivalent radius of the target satellite, r j Indicates the j The equivalent radius of an obstacle, V j Indicates that the target satellite and the j The relative speed of the obstacle, R j Indicates the target satellite and the j The equivalent collision radius of obstacles, Indicates the target satellite and the j The effective time window for the relative interaction of obstacles, d j represents the minimum approach distance, represents the speed error, Indicates position error.

3. The method according to claim 1, characterized in that The operation of constructing a consumption calculation model according to the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite includes: The consumption calculation model is constructed according to the following formula : ， in represents the altitude adjusted by the target satellite to avoid collision, Ps ( ) represents the probability that the target satellite does not collide after adjusting the altitude, E ( ) represents the energy value consumed by the target satellite to adjust its altitude, K Indicates the error value.

4. The method according to claim 1, characterized in that Taking minimum consumption as the goal, solving the consumption calculation model by means of a genetic algorithm to determine the operation of adjusting the altitude of the target satellite includes: Determining the number of binary bits of an initial population of a plurality of chromosomes of the genetic algorithm according to the movable range and the moving precision of the target satellite, wherein the moving precision is used to indicate the unit length of the movement of the target satellite; Generate a binary-based initial population according to the binary digit number, wherein the initial population is an initial adjustment height of the target satellite; and The consumption calculation model is solved according to the initial population to determine the adjustment altitude of the target satellite.

5. The method according to claim 4, characterized in that The operation of determining the number of binary bits of an initial population composed of a plurality of chromosomes of the genetic algorithm according to the movable range and the moving accuracy of the target satellite comprises: The number of binary digits of the initial population is determined according to the following formula n : ， in U represents the maximum distance to which the target satellite is adjusted upwards, L represents the maximum distance to which the target satellite is adjusted downward, SA Indicates the moving accuracy of the target satellite.

6. The method according to claim 4, characterized in that The operation of determining the adjusted altitude of the target satellite comprises: Determining a chromosome binary string corresponding to the adjustment height according to the consumption calculation model; and The chromosome binary string is decoded by the following formula to determine the adjustment height: ， ， in represents the precision parameter, represents the chromosome binary string i Number of digits, n represents the number of bits of the chromosome binary string, U represents the maximum distance to which the target satellite is adjusted upwards, L Indicates the maximum distance that the target satellite is adjusted downward.

7. A satellite collision avoidance device, characterized in that: include: An information acquisition module, used to acquire obstacle information within the movable range of the target satellite, wherein the obstacle information includes position information, speed information and volume information of the obstacle; A probability calculation module, used to calculate the probability that the target satellite does not collide with the obstacle according to the obstacle information and the target satellite information, wherein the target satellite information includes the position information, speed information and volume information of the target satellite; An energy value calculation module, used to calculate the energy value consumed by the target satellite according to the altitude adjusted by the target satellite to avoid collision; A model building module, used to build a consumption calculation model according to the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite; as well as The height determination module is used to solve the consumption calculation model by genetic algorithm with the minimum consumption as the goal, and determine the adjustment height of the target satellite, wherein: The probability calculation module includes: a first calculation submodule, used to calculate the minimum approach distance between the target satellite and the obstacle according to the position information of the target satellite and the position information of the obstacle; and a second calculation submodule, used to calculate the probability that the target satellite and the obstacle do not collide according to the minimum approach distance and the speed information and volume information of the target satellite and the obstacle.

8. A satellite collision avoidance device, characterized in that: include: processor; as well as A memory, connected to the processor, configured to provide the processor with instructions for processing the following processing steps: Obtaining obstacle information within the movable range of the target satellite, wherein the obstacle information includes position information, speed information, and volume information of the obstacle; Calculating the probability that the target satellite does not collide with the obstacle according to the obstacle information and the target satellite information, wherein the target satellite information includes the position information, speed information and volume information of the target satellite; Calculating the energy value consumed by the target satellite according to the altitude adjusted by the target satellite to avoid collision; constructing a consumption calculation model according to the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite; and Taking minimum consumption as the goal, the consumption calculation model is solved by a genetic algorithm to determine the adjustment height of the target satellite, wherein: The operation of calculating the probability that the target satellite does not collide with the obstacle based on the obstacle information and the target satellite information includes: calculating the minimum approach distance between the target satellite and the obstacle based on the position information of the target satellite and the position information of the obstacle; and calculating the probability that the target satellite does not collide with the obstacle based on the minimum approach distance and the speed information and volume information of the target satellite and the obstacle.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to claim 1 are implemented.

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